A transmitter sends a signal over a medium. A receiver obtains the signal transmitted over the medium and converts it to meaningful information, for example by demodulating the signal. Since information is often expressed in a digital form, for example as a stream of finite values of data, transmitters often send digitally modulated signals wherein the signals are modulated according to information expressed in a digital form.
Various modulation techniques have been developed to efficiently transmit information expressed in a digital form. These include amplitude modulation and phase modulation. For example, quadrature phase shift keying (QPSK), π/4 (pi over four) DQPSK, and M-level quadrature amplitude modulation (QAM) are a few such techniques. These techniques define a constellation of symbols, where each symbol may be used to communicate a plurality of bits of data. The symbols are identified based on their position on an I/Q plane. To receive a signal modulated according to one of these techniques, a receiver distinguishes the position of one symbol in the I/Q plane from the positions of other symbols.
The number of symbols in a constellation may be defined as whatever level is appropriate. For example, a QPSK system provides a constellation of four symbols. QAM systems may be defined to have constellations of 16 symbols (16 QAM), 64 symbols (64 QAM), or 256 symbols (256 QAM). One skilled in the art would recognize the multitude of variations that are possible based on the locations of symbols of a signal on an I/Q plane from amplitude modulation, phase modulation, or a combination of amplitude and phase modulation.
Unfortunately, various types of impairments may affect the location of a received symbol on the I/Q plane. For example, phase noise, such as that introduced by receiving or transmitting circuits, results in an angular displacement of symbol locations with respect to the origin of the I/Q plane and the ideal symbol coordinates. As another example, continuous wave (CW) noise changes the appearance of the symbols over time from single points to circles. As a further complication, multiple types of impairment may be present simultaneously. For example, If phase noise occurs in combination with CW noise, the circles attributed to the CW noise may be elongated to more of an elliptical or crescent shape by the influence of the phase noise. All of these types of impairments can be further obscured on the I/Q plane by the presence of additive white Gaussian noise.
If impairment is sufficient to cause ambiguity as to the location of a symbol, an error can occur when the signal is received. For a digitally-modulated signal to be converted to meaningful information, it is processed and applied to a data slicer. The data slicer makes a hard decision as to the data understood to be represented by the signal. When severe impairment exists, the data slicer may misidentify the data represented by the symbol, resulting in an error in the received hard decision data. To obtain correct data, the error will have to be corrected according to an error correction protocol or the data will have to be retransmitted or considered lost. Such errors adversely affect the data rate capability between the transmitter and the receiver, thereby reducing system performance.
In the prior art, it was necessary to manually connect specialized test equipment to a receiver in an attempt to understand impairment. However, the specialized test equipment had to be observed by skilled personnel who would attempt to understand the information displayed on the specialized test equipment. Since the specialized test equipment provided a display of information relating to a specific point in time, analysis of impairment behavior over time was possible only if the skilled personnel observed the specialized test equipment over time and were able to mentally process the information with the hope of correlating the impairment information.
Unfortunately, combinations of different types of impairment often obscured the understanding of the true nature or weight of the individual impairments. Moreover, boredom and strain on the skilled personnel interfered with accurate observation over time. Furthermore, no technique was provided to display impairment information gathered over time in a manner that allows interpretation of the historic nature of the impairments. Also, no technique was provided to display the severity and other characteristics of a particular type of impairment.
Another problem of prior art techniques is that they usually involve interruptions of service when test equipment is connected to a system under test. Such interruptions can increase customer dissatisfaction in addition to dissatisfaction resulting from the impairments being analyzed.
Communication links transmitting bursts of data (“bursty data”) are difficult to analyze, and information provided by prior art test equipment will be ambiguous for such communication links because of the lack of continuously received data. Moreover, bursty data from multiple service areas, subnets, subscribers, or transmission sources make analysis using prior art techniques practically impossible, as signal qualities will be the superposition of all such sources.
Thus, a technique is needed to identify impairment of a digitally-modulated signal in a manner that avoids the disadvantages of the prior art.